Is there any difference between a control and an action in reinforcement learning?
There's no difference. As they too often do, ML researchers take concepts from other disciplines, conveniently forget to cite sources and change the terminology, leading to much confusion. RL is a textbook example (pun intended). Optimal control researchers have been studying very similar problems long before RL ones, and used standard symbols and terms ($x$ for states, $u$ for controls). Then RL researchers came and changed just about everything. 

See the paper A Tour of Reinforcement Learning: The View from Continuous Control (2018), by Benjamin Recht, which discusses reinforcement learning from a control and optimization perspective.

See also this tweet https://twitter.com/beenwrekt/status/1134536093980864514?s=21 (by Benjamin Recht) regarding the presentation of Sham Kakade.